My goal is to build intelligent machines based on concepts of the human brain,
and evaluate them in complex simulations. Currently, I’m focusing on agents
that learn without rewards, model-based reinforcement learning, and variational
inference.

Short biography

Danijar Hafner is a PhD candidate at the University of Toronto under the
supervision of Jimmy Ba, where he focuses on designing agents that learn
without rewards. Danijar obtained his MRes at the University College London and
Gatsby Unit under the supervision of Timothy Lillicrap and Karl Friston. He is
also a student researcher at Google Brain. Danijar co-authored the book
“TensorFlow for Machine Intelligence” and advises Stanford’s course “TensorFlow
for Deep Learning Research”. He completed his bachelor’s thesis on deep
reinforcement learning for the video game Doom at the Hasso Plattner Institute,
Germany.